Cross Lingual Natural Language Inference On 1
Metrics
Accuracy
Results
Performance results of various models on this benchmark
Model Name | Accuracy | Paper Title | Repository |
|---|---|---|---|
| BERT | 74.3% | BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding | |
| X-CBOW | 60.7% | Supervised Learning of Universal Sentence Representations from Natural Language Inference Data | |
| X-BiLSTM | 68.7% | Supervised Learning of Universal Sentence Representations from Natural Language Inference Data | |
| XLM-R R4F | 85.2% | Better Fine-Tuning by Reducing Representational Collapse |
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